NR 322: Interpolation

Jim Graham

Fall 2008

Chapters 7 and 8

US Temperature Range

Map of Species Richness

Interpolation

• Interpolation is a method of constructing new data points within the range of a discrete set of known data points.

Interpolation (IDW)

Simple Interpolation

Mea

sure

d V

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Spatial Cross-section

50

3540

20

Simple Interpolation

Mea

sure

d V

alue

s

Spatial Cross-section

50

3540

20

Simple Interpolation

Mea

sure

d V

alue

s

Spatial Cross-section

50

3540

20

55 4247 36 36 37 38 40 34 28 21

Spline Interpolation

Mea

sure

d V

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s

Spatial Cross-section

50

3540

20

55 4248 35 35 37 38 40 36 28 22

First law of Geography

• Everything is related to everything else, but near things are more related than distant things

• TOBLER, W. R. (1970). "A computer movie simulating urban growth in the Detroit region". Economic Geography, 46(2): 234-240.

Process

• Obtain points with measurements

• Interpolate between the points using:– Inverse Distance Weighting– Kriging– Splines

• Convert the raster to vector using contours

Vector (Points) to Rater

• Interpolation– IDW– Kriging– Splines

• Density

Inverse Distance Weighting

• Points closer to the pixel have more “weight”

IDW – Variable Radius

IDW – Fixed Radius

Inverse Distance Weighting

Spline

• Spline type: Tension

• Increase “Weight” or decrease the “Number of points”

Splines

Kriging

• See the Geostatistical Analyst

• NR/ST523 - Quantitative Spatial Analysis

• NR512 - Introduction to Spatial Statistical Modeling of Natural Resources

Kriging

Geostatistical Analyst

• Provides much more control over interpolation